Systems and methods for optimizing wireless network coverage, capacity, and throughput

ABSTRACT

A network device receives one or more first key performance indicators (KPIs) associated with a cell site providing wireless service within a geographic area and determines at least one first capacity usage parameter associated with the cell site providing the wireless service. The network device determines placement of an additional antenna array within the geographic area to provide a certain coverage and capacity for the geographic area based on the one or more first KPIs and the determined at least one first capacity usage parameter.

RELATED APPLICATION

The present application is a continuation of, and claims priority to,U.S. application Ser. No. 16/286,977 entitled “Systems and Methods forOptimizing Wireless Network Coverage, Capacity, and Throughput” filedFeb. 27, 2019, the contents of which are incorporated by referenceherein in their entirety.

BACKGROUND

Next Generation mobile networks, such as Fifth Generation (5G) mobilenetworks, are expected to operate in the higher frequency ranges, andsuch networks are expected to transmit and receive in the GigaHertz bandwith a broad bandwidth near 500-1,000 MegaHertz. The expected bandwidthof Next Generation mobile networks is intended to support downloadspeeds of up to about 35-50 Gigabits per second. The proposed 5G mobiletelecommunications standard, among other features, operates in themillimeter wave bands (e.g., 14 GigaHertz (GHz) or higher), and supportsmore reliable, massive machine communications (e.g., machine-to-machine(M2M), Internet of Things (IoT), etc.). Next Generation mobile networks,such as those implementing the 5G mobile telecommunications standard,are expected to enable a higher utilization capacity than currentwireless systems, permitting a greater density of wireless users, with alower latency. Next Generation mobile networks, thus, are designed toincrease data transfer rates, increase spectral efficiency, improvecoverage, improve capacity, and reduce latency.

Millimeter wave (mmWave) frequencies are proposed to be used in advancedwireless systems, such as, for example, 5G systems. mmWave frequencies,however, have limited building penetration as compared to lowerfrequency waves. Due to this limited building penetration, cell sitescontaining the system antennas will need to be close to the network userto make up for the signal losses through buildings. This requires agreater cell density in the advanced wireless systems, relative tocurrent systems. Additionally, to satisfy the improved utilizationcapacity requirements of advanced wireless systems, a greatly increasednumber of antennas, relative to current systems (e.g., Fourth Generation(4G) systems), will need to be deployed to support high bandwidthconnections to each wireless device. In current wireless systems, thetypical distance between adjacent antennas is about 1.5-3.2 kilometers(km). In contrast, for proposed advanced wireless systems, such as 5Gsystems, the distance between adjacent antennas may need to be reducedto about 200-300 meters. Therefore, next generation wireless systems mayneed as many as one hundred times the number of antennas as compared tocurrent wireless systems.

Multiple-input and multiple-output (MIMO) is a technique for usingmultiple transmit and receive antennas to multiply the capacity of aradio link and exploit multipath propagation. MIMO is a component ofwireless communication standards such as Wi-Fi (IEEE 802.11n & IEEE802.11ac), WiMAX (4G) and Long-Term Evolution (4G). Full dimension MIMO(FD-MIMO) involves multiple transmit and receive antennas that can formbeams in both horizontal and vertical directions such that the beams cancover anywhere in three-dimensional space in the vicinity of themultiple antennas. Massive MIMO involves a MIMO system that utilizes avery large number of antennas. The more antennas a massive MIMO systemhas, the more possible signal paths the system has and the better thesystem's performance in terms of data rate and link reliability.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an overview of an exemplary network environment inwhich wireless network coverage, capacity, and throughput is optimizedby a centralized node that monitors various wireless network performanceparameters;

FIGS. 2A-2C depict examples of beam forming to create antenna beampatterns in three dimensions in the vicinity of an antenna array;

FIG. 3 depicts an example of a deployment of an antenna array in athree-dimensional physical environment;

FIG. 4 depicts a simplified example of an antenna array associated witha cell site that provides at least a portion of the wireless networkcoverage shown in FIG. 1;

FIG. 5 depicts an overhead view of an example of a more complex cellsite associated with providing at least a portion of the wirelessnetwork coverage shown in FIG. 1;

FIG. 6 depicts baseband processing components of a base station, andtransmitter/receiver and power amplification components associated withan antenna array, according to an exemplary implementation;

FIG. 7 is a diagram that depicts exemplary components of a device thatmay correspond to the UEs, base stations, and the wireless networkoptimizer of FIG. 1;

FIGS. 8A and 8B are flow diagrams that illustrate an exemplary processfor optimizing wireless network coverage, capacity, and throughput basedon network service Key Performance Indicators;

FIG. 9 is a flow diagram that illustrates an exemplary process fordetermining the need for an additional antenna array(s) in a geographicarea to provide adequate wireless network coverage and capacity;

FIG. 10 is a flow diagram that illustrates an exemplary process fordetermining an optimum location(s) within a geographic area for addingan additional antenna array(s); and

FIGS. 11A and 11B are flow diagrams that illustrate an exemplary processfor dynamically setting a handover threshold to optimize networkthroughput within an area of a wireless network.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following detailed description refers to the accompanying drawings.The same reference numbers in different drawings may identify the sameor similar elements. The following detailed description does not limitthe invention, which is defined by the claims.

Fifth Generation (5G) radio deployments at mmWave frequencies requiremore line of sight antenna installations as compared to current FourthGeneration (4G) radio deployments. Additionally, 5G cell deploymentswill be much denser than current 4G cell deployments, and mmWave 5Gantennas will be much smaller and more directional than 3G or 4Gantennas. Furthermore, 5G antennas are expected to be deployed on poles,lamp posts, bus stops, and other more open locations, that are moresusceptible to environmental and human impacts that may negativelyaffect the deployment environment of the antennas. For example, in 5Gradio deployments, deviation of antennas from their optimal deploymentangles can have a detrimental effect on quality of service. To maintaingood wireless network performance, given the characteristics of 5G radiodeployments, a more proactive approach that includes a high level ofperformance monitoring will be required.

Exemplary embodiments described herein implement a central node,employing dynamic intelligent processes, that performs on-goingmonitoring of different wireless network key performance indicators, andwhich executes the dynamic processes for optimizing wireless networkcoverage, capacity, and throughput based on the monitored keyperformance indicators. Optimization of the wireless network coverageand capacity involves the continuous, or periodic, monitoring of thenetwork key performance indicators, and the dynamical alteration of thenumber, and location, of antenna arrays of the cell sites within ageographic area based on the monitored key performance indicators.Optimization of wireless network throughput may involve adjusting thehandover threshold between cell sites (in addition to many otherfactors), in a dynamic fashion, based on the monitored key performanceindicators.

FIG. 1 illustrates an overview of an exemplary network environment 100in which wireless network coverage, capacity, and throughput isoptimized by a central node that monitors various wireless networkperformance parameters. As shown, network environment 100 includesmultiple base stations 105-1 through 105-x, multiple antenna arrays 110,multiple user equipment devices (UEs) 115-1 through 115-y, a wirelessnetwork optimizer 130, and one or more networks 140.

Base stations 105-1 through 105-x (referred to herein as “base station105” or “base stations 105”) may each include a base station of a PublicLand Mobile Network (PLMN), or other type of wireless station, thatconnects to one or more antenna arrays 110 and controls the transmissionand reception of data via a wireless interface. Each of base stations105 may include, for example, a Node B, an Evolved Node B (eNB), or aNext Generation Node B (gNB) of a PLMN (e.g., Third Generation (3G),Fourth Generation (4G), or Fifth Generation (5G) PLMN) that furtherincludes the hardware that communicates between other nodes of the PLMNand mobile devices (i.e., UEs) that are located within the antenna beampatterns formed by respective antenna arrays 110.

Each base station 105 may, in some implementations, be split intovarious components and located in a distributed fashion. For example,base station 105 may be split into a base band unit (BBU) and multipleremote radio heads (RRHs), where the BBU may be located at a differentlocation than the RRHs and may connect to the RRHs via, for example,optical fibers. Each BBU includes a network device that operates as thedigital function unit that transmits digital baseband signals to themultiple RRHs, and receives digital baseband signals from the multipleRRHs. If the BBU is connected to the multiple RRHs via, for example,optical fibers, then the BBU may convert the digital baseband signalsinto corresponding optical signals for transmission to the RRHs, and mayreceive optical signals from the RRHs and convert the optical signalsinto corresponding digital baseband signals. The RRHs include networkdevices that operate as radio function units that transmit and receiveradio frequency (RF) signals to/from UEs (e.g., UE 115). If the RRHs areconnected to the BBU via an optic fiber, the RRHs may convert receivedRF signals to optical signals, and transmit the optical signals to theBBU. Additionally, the RRHs may receive optical signals from the BBU viathe optic fiber, convert the optical signals to RF signals fortransmission via one or more antenna arrays of the RRHs. Each of theRRHs may include at least one antenna array, transceiver circuitry, andother hardware and software components for enabling the RRHs to receivedata via wireless RF signals from UEs 115, and to transmit wireless RFsignals to UEs 115. Therefore, a “base station,” as referred to herein,may include a BBU interconnected with multiple RRHs.

Antenna arrays 110 (referred to herein as “antenna array 110” or“antenna arrays 110”) may each include an array of antennas, such as,for example, a FD-MIMO or massive MIMO antenna array, that may formantenna beams in horizontal and/or vertical directions to enable eacharray of antennas to cover a three-dimensional space in the vicinity ofeach array 110. For example, each antenna array 110 may include a numberof horizontal antennas and a number of vertical antennas arranged in arow(s) and column(s) configuration. As an example, an antenna array 110may include a 2×4 array with the number of vertical antennas equalingthe number of rows (e.g., 2) and the number of horizontal antennasequaling the number of columns (e.g., 4). Alternatively, each antennaarray 110 may include an m×n (m rows by n columns), where m is a numberof vertical antennas in the array 110 and n is a number of horizontalantennas in the array 110, m and n may be any positive integer greaterthan or equal to one, and m and n may or may not equal one another. Theantenna arrays 110 shown in FIG. 1 may produce a wireless networkcoverage area 120 within which UEs 115 may transmit to, and receivefrom, antenna arrays 110 via wireless transmissions. The wirelessnetwork coverage area 120 may provide reliable wireless connections overa particular geographic area and have a certain maximum capacity andthroughput.

A “cell site,” as referred to herein, includes a base station 105, andthe one or more antenna arrays 110 to which base station 105 connectsand that are used by the base station 105 for transmitting data to UEs115, and for receiving data from UEs 115. As shown in FIG. 1, basestation 105-1 and connected antenna array(s) 110 represent cell site125-1, base station 105-2 and connected antenna array(s) 110 representcell site 125-2, and base station 105-x and connected antenna array(s)110 represent cell site 125-x. Each cell site 125 provides wirelessnetwork coverage in a particular geographic area based on the antennabeams of the antennas of each antenna array 110. Each antenna of theantenna arrays 110 may form a single beam of radio coverage. In someimplementations, each antenna may use a series of antenna elements toform the single beam of radio coverage. As described above, in someimplementations, each base station 105 may include multiple distributedcomponents (e.g., a BBU and multiple RRHs).

UEs 115-1 through 115-y (referred to herein as “UE 115” or “UEs 115”)each includes any type of device having one or more wirelesscommunication interfaces for communicating via antenna arrays 110, basestations 105, and network 140. The UEs 115 may each include, forexample, a cellular radiotelephone; a smart phone; a personal digitalassistant (PDA); a wearable computer; a Machine-to-Machine (M2M) device;an Internet of Things (IoT) device; a desktop, laptop, palmtop or tabletcomputer; or a media player. Each UE 115 may connect to network 140 viaa wireless connection. A “user” (not shown in FIG. 1) may be associatedwith each UE 115, and may be an owner, operator, and/or a permanent ortemporary user of the UE 115.

Wireless network optimizer 130 may include one or more network devicesthat performs intelligent processes for optimizing the coverage,capacity, and throughput of a wireless network(s), such as, for example,a PLMN of network(s) 140. Wireless network optimizer 130 may, forexample, perform the processes described below with respect to FIGS.8A-11B to optimize the coverage, capacity, and throughput of thewireless network.

Networks 140 may include one or more networks of various types, with atleast one network including a wireless network, such as, for example, aPLMN or a satellite mobile network. The PLMN may include a Code DivisionMultiple Access (CDMA) 2000 PLMN, a Global System for MobileCommunications (GSM) PLMN, a Long Term Evolution (LTE) PLMN, and/orother types of PLMNs. In addition to at least one wireless network,network(s) 140 may further include a telecommunications network (e.g.,Public Switched Telephone Networks (PSTNs)), a wired and/or wirelesslocal area network (LAN), a wired and/or wireless wide area network(WAN), a metropolitan area network (MAN), an intranet, the Internet,and/or a cable network (e.g., an optical cable network).

The configuration of the components of network environment 100 depictedin FIG. 1 is for illustrative purposes only, and other configurationsmay be implemented. Therefore, network environment 100 may includeadditional, fewer and/or different components, that may be configureddifferently, than depicted in FIG. 1.

FIGS. 2A-2C depict examples of beam forming to create an antenna beampattern in three dimensions in the vicinity of an antenna array 110. Theexample of FIG. 2A depicts a single antenna beam pattern 200 formedhorizontally and vertically by a single antenna in an antenna array 110.Thus, as shown in FIG. 2A, an antenna, such as the antenna residing atthe intersection of the third row and second column of the antennaarray, may be configured to generate the antenna beam pattern 200 thatextends downwards at a particular angle from the antenna.

The example of FIG. 2B depicts three antenna beam patterns 210-1, 210-2and 210-3 formed horizontally and vertically by three different antennasin an antenna array 110. As shown in FIG. 2B, three antennas, residingadjacent one another in a single column of the antenna array 110, may beconfigured to generate a respective antenna beam pattern 210-1, 210-2,and 210-3 at a different angle (i.e., different elevation) relative tothe position of each antenna's respective row within the antenna array110.

The example of FIG. 2C further depicts six antenna beam patterns 220-1,220-2, 210-3, 220-4, 220-5 and 220-6 formed horizontally and verticallyby six different antennas in an antenna array 110. As shown in FIG. 2C,three antennas, residing adjacent one another in a single column of theantenna array 110, may be configured to generate a respective antennabeam pattern 220-2, 220-2, and 220-3 at a different angle (i.e.,different elevation) relative to the position of each antenna'srespective row within the antenna array 110. As further shown in FIG.2C, three additional antennas, residing adjacent one another in a singlerow of the antenna array 110, may be configured to generate a respectiveantenna beam pattern 220-4, 220-5 and 220-6 at a different angle (i.e.,different azimuth) relative to the position of each antenna's respectivecolumn within the antenna array 110.

FIG. 3 depicts an example of a deployment of an antenna array 110 in athree-dimensional physical environment 300. As shown in FIG. 3, thethree-dimensional physical environment 300 includes various natural andman-made features (e.g., trees and buildings) among which various typesof UEs 115 reside and wirelessly receive data via respective antennabeams of antenna array 110.

FIG. 4 depicts a simplified example of an antenna array 110 associatedwith a cell site 400 that provides at least a portion of the wirelessnetwork coverage 120 shown in FIG. 1. As shown, an antenna array 110,via respective antenna beams of the antennas of the array, generates awireless network coverage area 410. The wireless network coverage area410 may be composed of multiple cells that are produced by respectiveantenna beam patterns associated with each of the antennas of antennaarray 110. FIG. 4 depicts a simplified example in which eight antennabeams generate respective overlapping cells (numbered 1 through 8) thatproduce the wireless network coverage area 410. Thus, a UE 115 (notshown) may transit between cells (e.g., between cell 1 and cell 6, orbetween cell 1 and cell 5), and the wireless network enables wirelessnetwork service to continue by “handing off” the UE 115 from one cell tothe next.

FIG. 5 depicts an overhead view of an example of a more complex cellsite 500 associated with providing at least a portion of the wirelessnetwork coverage 120 shown in FIG. 1. The cell site 500 includes anantenna array 110 (not shown) that generates a beam map 510 associatedwith a wireless network coverage area composed of multiple cells thatare produced by respective antenna beam patterns associated with each ofthe antennas of antenna array 110. In the example cell site 500 of FIG.5, thirty-two antenna beams generate respective overlapping cells(numbered 1 through 32) that produce the wireless network coverage areaof the beam map 510. Generally, a given cell site in a wireless networkmay produce a beam map 510 composed of n cells (where n is any positiveinteger greater than or equal to one) that are arranged in any patternor configuration that ensures wireless service coverage in theparticular area of the cell site.

FIG. 6 depicts baseband processing components of a base station 105, andtransmitter/receiver and power amplification components associated withan antenna array 110, according to an exemplary implementation. In animplementation in which base station 105 is split into distributedcomponents, such as a base band unit (BBU) and multiple remote radioheads (RRHs), baseband processor 610 may be a component of the BBU andthe components of the antenna array 110 may further be components of aRRH. As shown, a baseband processor 610 of the base station 105 connectsto components associated with an antenna array 110. The components ofthe antenna array 110 include a block transmitter/receiver and poweramplifier (Tx/Rx+PA) 620, a weight vector 630, and multiple connectors640-1 through 640-x for connecting to respective antennas 1 through x ofan antenna array 110 (not shown) having x antennas.

Baseband processor 610 of base station 110 includes a device (e.g., achip or part of a chip) in a network interface that manages radiofunctions that require the use of antenna array 110. Baseband processor610 may include, in addition to other components, its own memory andsoftware/firmware components. Tx/Rx+PA 620 may include a transmitter fortransmitting via one or more antennas of the antenna array 110, areceiver for receiving via one or more antennas of the antenna array110, and a power amplifier for amplifying signals transmitted, orreceived, via antennas of the antenna array 110. Weight vector unit 630includes a device(s) for applying x weighted values to signalstransmitted or received via the respective x antennas of the antennaarray 110. Connectors 640-1 through 640-x each include a connectormechanism for electrically connecting a respective antenna of theantenna array 110 to a respective weight vector unit 630.

The configuration of the components of base station 105 and antennaarray 110 depicted in FIG. 6 is for illustrative purposes only, andother configurations may be implemented. Therefore, base station 105and/or antenna array 110 may include additional, fewer and/or differentcomponents, that may be configured differently, than depicted in FIG. 6.Though components for only a single antenna array 110 are shown in FIG.6, baseband processor 610 may connect to multiple, different antennaarrays 110.

FIG. 7 is a diagram that depicts exemplary components of a device 700.UEs 115, base stations 105, and wireless network optimizer 130 may eachinclude the same, or similar, components to those of device 700 shown inFIG. 7. Device 700 may include a bus 710, a processing unit 720, a mainmemory 730, a read only memory (ROM) 740, a storage device 750, an inputdevice(s) 760, an output device(s) 770, and a communication interface(s)780.

Bus 710 includes a path that permits communication among the componentsof device 700. Processing unit 720 may include one or more processors ormicroprocessors, or processing logic, which may interpret and executeinstructions. Main memory 730 may include a random access memory (RAM)or another type of dynamic storage device that may store information andinstructions for execution by processing unit 720. ROM 740 may include aROM device or another type of static storage device that stores staticinformation and instructions for use by processing unit 720. Storagedevice 750 may include a magnetic and/or optical recording medium. Mainmemory 730, ROM 740 and storage device 750 may each be referred toherein as a “non-transitory computer-readable medium” or a“non-transitory storage medium.”

Input device(s) 760 may include one or more mechanisms that permit auser to input information to device 700, such as, for example, a keypador a keyboard, a display with a touch sensitive panel, voice recognitionand/or biometric mechanisms, etc. Output device(s) 770 may include oneor more mechanisms that output information to the user, including adisplay (e.g., with a touch sensitive panel), a speaker, etc. Inputdevice(s) 760 and output device(s) 770 may be implemented as a graphicaluser interface (GUI) (e.g., a touch screen GUI that uses any type oftouch screen device) that displays GUI information and which receivesuser input via the GUI. Communication interface(s) 780 may include atransceiver that enables device 700 to communicate with other devicesand/or systems. For example, communication interface(s) 780 may includewired and/or wireless transceivers for communicating via network 130.

The configuration of components of device 700 shown in FIG. 7 is forillustrative purposes. Other configurations may be implemented.Therefore, device 700 may include additional, fewer and/or differentcomponents, arranged in a different configuration, than depicted in FIG.7.

FIGS. 8A and 8B are flow diagrams that illustrate an exemplary processfor optimizing wireless network coverage, capacity, and throughput basedon network service Key Performance Indicators (KPIs). The exemplaryprocess of FIGS. 8A and 8B may be implemented by wireless networkoptimizer 130, in conjunction with one or more antenna arrays 110. Theexemplary process of FIGS. 8A and 8B may be repeated for each cell site125 within a wireless network. Wireless network optimizer 130 may, thus,be concurrently executing a different instance of the process of FIGS.8A and 8B for each cell site 125 within the wireless network (e.g.,within a PLMN).

The exemplary process includes wireless network optimizer 130 receivinga first set of cell service Key Performance Indicators (KPIs) from aserving base station 105 of a cell site (block 800). The KPIsmeasured/determined by the serving base station 105 of the cell site mayinclude, for example, the average active time per beam (ATavg), thereceive signal strength per beam (Reference Signal Received Power(RSRP_(rcv))), the receive Signal-to-Noise-Plus-Interference Ratio(SINR_(rcv)) per beam, the Radio Resource Control (RRC) setup time(RRC_(st)), and RRC setup failure rate (RRC_(sfr)). Other KPIs, measuredor determined by the serving base station 105, may additionally, oralternatively, be sent to the wireless network optimizer 130. Theaverage active time per beam (ATavg) includes an average of activetransmission time per beam (i.e., per antenna of the antenna array 110).The receive signal strength per beam (RSRP_(rcv)) includes the RSRP ofsignals received via each beam (i.e., via each antenna of the antennaarray 110). The Signal-to-Noise-Plus-Interference Ratio (SINR_(rcv)) perbeam includes the measured SINR of signals received via each beam (i.e.,via each antenna of the antenna array 110). The Radio Resource Control(RRC) setup time (RRC_(st)) includes a determined time for setting upconnections between UEs 115 and the antenna arrays 110 of the servingbase station 105. The RRC setup failure rate (RRC_(sfr)) includes adetermined rate associated with failures to set up connections betweenUEs 115 and the antenna arrays 110 of the serving base station 105.

Wireless network optimizer 130 receives a second set of cell serviceKPIs from UEs 115 via the base station 105 of the cell site (block 805).Each UE 115 measures/determines a receive signal strength of neighboringcell sites (RSRR_(nc)), and a SINR of neighboring cell sites(SINR_(nc)), and reports those measurements to the serving base station105 which, in turn, forwards those measurements to wireless networkoptimizer 130.

Wireless network optimizer 130 determines a current cell capacity usage(“Cell Capacity”) for the cell site (block 810) using, for example,Equation (1):Cell Capacity=∫_(b=0) ^(B)∫_(t=0) ^(T)∫_(u=0)^(U)ƒ(t,ATavg,Modulation(SINRu))  Eqn. (1)where t=time,

-   -   T=a current time interval,    -   ATavg=average active time per beam of the cell site's antenna        array during the current time interval T,    -   u=user equipment (UE),    -   Modulation(SINRu)=modulation scheme employed by a UE u having a        certain Signal-to-Noise-Plus-Interference Ratio (SINR_(u)),    -   b=a beam of the cell site's antenna array,    -   B=maximum number of beams of the cell site's antenna array, and    -   U=a number of UEs being served by the cell site during the        current time interval T.        The current cell capacity usage of Eqn. (1) may be used to        determine the current amount of usage, over the time interval T,        by U UEs 115 receiving wireless service via B beams of the        antenna array(s) 110 of the serving base station 105.

Wireless network optimizer 130 may determine a need for an additionalantenna array(s) to provide adequate coverage and capacity for thegeographic area served by the cell site based on the determined currentcell capacity usage and the first and/or the second set of cell serviceKPIs (block 815). Wireless network optimizer 130 analyzes the currentcell capacity usage (Eqn. (1)) for the cell site, and the first and/orsecond set of cell service KPIs, to determine the need to add one ormore additional antenna arrays 110 for improving the coverage andcapacity in the geographic area. Details of one exemplary implementationof block 815 is described further below with respect to the process ofFIG. 9.

If an additional antenna array(s) 110 is determined in block 815 to notbe needed (NO—block 820), then the exemplary process continues at block840 below (FIG. 8B). If an additional antenna array(s) 110 is determinedin block 815 to be needed (YES—block 820), then wireless networkoptimizer 130 determines an optimum location(s) within the geographicarea of the cell site 125 for adding the additional antenna array(s)(block 825). Determination of an optimum location(s) for placement of anadditional antenna array(s) may be based on a number of differentfactors, including UE distribution (e.g., per beam and/or in space andtime) within the geographic area served by the cell site, beam datacapacity usage per beam of the current antenna array(s) of the cellsite, and a beam map of the cell site. Details of one exemplaryimplementation of block 825 is described further below with respect tothe process of FIG. 10.

Wireless network optimizer 130 verifies optimization of placement of theadditional antenna array(s) in the geographic area (block 830). Toverify optimization of the placement of the additional antenna array(s),wireless network optimizer 135 may repeat the process of FIG. 10,described below, with optimization of placement of the additionalantenna array(s) being verified if the identified location, in block1020, is within close proximity to the location at which the antennaarray(s) was previously added.

If placement of the additional antenna array(s) is not optimized(NO—block 835), then the exemplary process repeats at block 825, withwireless network optimizer 130 determining a different optimum locationwithin the geographic area for adding the additional antenna array(s).The different optimum location within the geographic area may bedetermined by repeating the process of FIG. 10, described below, toidentify a new location for placement of the additional antennaarray(s).

If placement of the additional antenna array(s) is optimized (YES—block835), then wireless network optimizer 130 determines whether there hasbeen an occurrence of changes in conditions that affect cell coverageand/or capacity in the geographic area served by the cell site,including structural, environmental, topographic, and/or other changes(block 840). Structural changes may include, for example, the additionor removal of physical structures (buildings, walls, highway ramps orother roadway structures), and changes in existing structures (e.g.,change in foundation of building affecting angle of reflection frombuilding surfaces). In one implementation, one or more cameras mayobtain images of an existing structure, and image analysis may beperformed by wireless network optimizer 130 to determine the type ofchange(s) in the existing structure, and to model the effect(s) of thetype of change(s). Environmental changes may include, for example,changes in the natural environment (e.g., trees have died, or been cutdown) that affect signal transmission within a certain area. Topographicchanges may include, for example, large scale changes to the topographythat may affect signal transmission (e.g., new roadway berms, or othertopographical changes to accommodate a roadway). Other changes mayinclude, for example, damage to a cell site (e.g., to a BBU or RRH of abase station), damage to an antenna array, movement of an antenna array,etc.

If there are changed conditions (YES—block 845), then the exemplaryprocess returns to block 800 (FIG. 8A) to re-determine the need forfurther additional antenna arrays. If there are no changed conditions(NO—block 845), then wireless network optimizer 130 dynamically sets thehandover threshold to optimize network throughput within the geographicarea (block 850). Dynamically setting the handover threshold may includeadjusting the threshold level at which handover occurs from a first cellof a first cell site to a second cell of a second cell site when a UE115 roams within a geographic area. Dynamic setting of the handoverthreshold may be based on a number of factors, such as, for example,current beam data usage per beam of an antenna array(s) 110 of thecurrent cell site; RRC_(sfr), RRC_(st), and cell capacity usage of thecurrent cell site; and RSRP_(nc), SINR_(nc) and beam data usage ofneighboring cell sites. Details of one exemplary implementation of block850 is described further below with respect to the process of FIGS. 11Aand 11B.

The exemplary process of FIGS. 8A and 8B may be repeated continuously,or periodically (e.g., at intervals specified by the mobile networkoperator), by wireless network optimizer 130 for each cell site 125 todynamically optimize wireless network service coverage, capacity, andthroughput to capture changes in the environment, changes in UEdistribution, changes in usage patterns, and/or changes in overallnetwork KPIs due to the optimization process itself. The dynamicoptimization of FIGS. 8A and 8B, therefore, adapts to new conditionsaffecting network service coverage, capacity, and throughput in thenetwork.

FIG. 9 is a flow diagram that illustrates an exemplary process fordetermining the need for an additional antenna array(s) in a geographicarea to provide adequate wireless network coverage and capacity. Theexemplary process of FIG. 9 represents one exemplary implementation ofblock 815 of the process of FIGS. 8A and 8B. The exemplary process ofFIG. 9 may be implemented by wireless network optimizer 130.

The exemplary process includes wireless network optimizer 130 setting amaximum beam data capacity usage per beam of the cell site (block 900).The maximum beam data capacity usage per beam of the cell site equalsthe maximum data capacity that may be served by a given beam (i.e.,antenna) of an antenna array 110 during a time interval T based on thefundamental performance constraints of the antenna and the base station105. A current beam data capacity usage per beam (“beam data capacity”)may be determined using Equation (2):Beam Data Capacity=∫_(t=0) ^(T)∫_(u=0)^(U)ƒ(t,ATavg,Modulation(SINRu))  Eqn. (2)where t=time,

-   -   T=a current time interval,    -   ATavg=average active time of the beam of antenna of antenna        array 110 during the current time interval T,    -   u=a user equipment (UE),    -   Modulation(SINRu)=modulation scheme employed by a UE u having a        certain Signal-to-Noise-Plus-Interference Ratio (SINR), and    -   U=number of UEs served by the beam of the antenna of the antenna        array 110 during the current time interval T.        The determined current beam data capacity per beam of an antenna        array 110, thus, may not exceed the maximum beam data capacity        per beam.

Wireless network optimizer 130 sets a maximum cell capacity usage(CellCap_(max)) of the site (block 905). CellCap_(max) for the antennaarray(s) 110 of a cell site is the maximum cell capacity that isavailable for UE use over a time interval T and is based on a maximumnumber of beams (i.e., antennas) available for the antenna array(s) 110.A current cell capacity usage for each cell site may be determined usingEqn. (1) above, and the current cell capacity usage may not exceedCellCap_(max).

Wireless network optimizer 130 determines a current beam data capacityusage for each beam of the cell site (block 910). Wireless networkoptimizer 130 may, for example, employ Eqn. (2) above to determine acurrent beam data capacity usage for each beam (i.e., for each activeantenna of the antenna array(s) 110) of the cell site. Wireless networkoptimizer 130 uses knowledge of the UEs 115 that receive wirelessservice over a time interval T, and knowledge of parameters of theantenna array 110, including the average active time per beam, themodulation scheme used by each of the UEs 115, and theSignal-to-Noise-Plus-Interference Ratio (SINR_(u)) for each of the UEs115.

Wireless network optimizer 130 determines a current cell capacity usagefor the cell site (block 915). Wireless network optimizer 130 may, forexample, employ Eqn. (1) above to determine a current cell site capacityusage for the cell site (i.e., for all of the antennas of the antennaarray(s) 110 of the cell site). Wireless network optimizer 130 usesknowledge of the UEs 115 that receives wireless service over a timeinterval T, and knowledge of parameters of the antenna array 110,including a number of beams (i.e., the number of antennas) in theantenna arrays(s) 110 of the cell site, the average active time perbeam, the modulation scheme used by each of the UEs 115, and theSignal-to-Noise-Plus-Interference Ratio (SINR_(u)) for each of the UEs115.

Wireless network optimizer 130 determines if the current cell capacityusage is greater than or equal to x % of the maximum cell capacity ofthe cell site (CellCap_(max)) (block 920). If the current cell capacityusage is not greater than or equal to x % of the CellCap_(max) (NO—block920), then the process returns to block 910, and repeats blocks 910,915, and 920. The value x may be preset or may be a dynamically varyingvalue that varies based on network conditions. In one example, x % maybe a fixed value of 80%. Other values of x, however, may be used.

If the current cell capacity usage is greater than or equal to x % ofCellCap_(max) (YES—block 920), then wireless network optimizer 130determines if the RRC setup failure rate (RRC_(sfr)) received from thebase station 105 is high, but the Reference Signal Received Power(RSRP_(rcv)) and Signal-to-Interference-plus-Noise Ratio (SINR_(rcv))reported by the base station 105 are at a sufficient level (block 925).If RRC_(sfr) is not high, or the RSRP_(rcv) and SINR_(rcv) are not at asufficient level (NO—block 925), then the process continues at block 840of FIG. 8B with an additional antenna array 110 not being added to thecell site. If RRC_(sfr) is high, and the RSRP_(rcv) and the SINR_(rcv)are at a sufficient level (YES—block 925), then the process continues atblock 825 of FIG. 8A with an additional antenna array(s) being added atthe cell site.

FIG. 10 is a flow diagram that illustrates an exemplary process fordetermining an optimum location(s) within a geographic area for addingan additional antenna array(s). The exemplary process of FIG. 10represents one exemplary implementation of block 825 of the process ofFIGS. 8A and 8B. The exemplary process of FIG. 10 may be implemented bywireless network optimizer 130.

The exemplary process includes wireless network optimizer 130determining a UE 115 distribution per beam for the geographic areacovered by the cell site (block 1000). Wireless network optimizer 130determines, for each beam of the cell site (i.e., each antenna in theantenna array(s) 110 of the cell site), the UEs 115 that are using thatbeam over a particular time interval. For example, beam ID_1 may bedetermined to be serving five UEs 115, beam ID_2 may be determined to beserving ten UEs 115, beam ID_3 may be determined to be serving three UEs115, and so on.

Wireless network optimizer 130 determines the beam(s) (i.e., antenna(s)of the antenna array(s) 110) of the cell site where the beam datacapacity usage, as a function of time, is high (block 1005). Wirelessnetwork optimizer 130 may use Eqn. (2) to determine the current beamdata capacity usage for each beam (i.e., each antenna) of the antennaarray(s) 110 of the cell site and may compare the determined currentbeam data capacity usage for each beam with a threshold value todetermine if the current beam data capacity usage exceeds the thresholdvalue. In one implementation, the threshold value may include an averagebeam data capacity usage value for the cell site.

Wireless network optimizer 130 analyzes the beam data capacity usage perbeam, and the beam map, in the geographic area of the cell site toidentify region(s) needing increased capacity (block 1010). Wirelessnetwork optimizer 130 may compare the current beam data capacity usagefor each beam, determined in block 1005, with a beam map thatcorresponds to the coverage area of the cell site, to determine areas ofthe beam map needing increased capacity. Referring to the example beammap 510 of the cell site 500 of FIG. 5, current beam data capacity usagefor beams 1, 2, 3, 14, 15, 16, 27, and 28 of the beam map 510 mayindicate high usage via those beams such that a high traffic area ofactive UEs 115 may be inferred within the geographic areas covered bythose beams.

Wireless network optimizer 130 determines the distribution in space andtime of UEs 115 within the geographic area covered by the cell site(block 1015). Wireless network optimizer 130 may generate a map thatidentifies UE IDs, and the location of those UEs, within the beam map ofthe cell site as a function of time. Therefore, a distribution of UEs115 within the cell site may be determined at any given time based onthe generated map.

Wireless network optimizer 130 identifies a location(s) for adding anantenna array(s) 110 based on the determined beam data capacity usage,the beam map, and the UE distribution (block 1020). The beam datacapacity usage determined in block 1105, the beam map analyzed in block1010, and the UE distribution determined in block 1015 may be used,among other factors, to identify a location(s) for adding an antennaarray(s) 110 for connection to the base station 110 of the cell site. Insome implementations, only a single location may be identified forlocating a single antenna array 110. In other implementations, multiplelocations may be identified at the cell site for locating multipleantenna arrays 110. In one implementation, the additional antennaarray(s) 110 may be manually installed at the determined optimumlocation(s) within the geographic area served by the cell site 125 basedon instructions received from wireless network optimizer 130.

FIGS. 11A and 11B are flow diagrams that illustrate an exemplary processfor dynamically setting a handover threshold to optimize networkthroughput within an area of a wireless network. The exemplary processof FIGS. 11A and 11B represents one exemplary implementation of block850 of the process of FIGS. 8A and 8B. The exemplary process of FIGS.11A and 11B may be implemented by wireless network optimizer 130.

The exemplary process includes wireless network optimizer 130 analyzingthe current beam data capacity usage for each beam of the cell site, theRRC_(sfr), RRC_(st), and the cell site's cell capacity usage todetermine if the serving cell site is too congested (block 1100).Threshold values may be established for the beam data capacityusage/beam, the RRC_(sfr), the RRC_(st), and the cell site cell capacityusage, and may be used for identifying whether currentlymeasured/determined values indicate congestion within the serving cellsite.

If the serving cell site is not too congested (NO—block 1105), thenblock 1100 may repeat. If the serving cell site is too congested(YES—block 1105), wireless network optimizer 130 obtains the RSRP_(nc),SINR_(nc), and beam data capacity usage of a neighboring cell site(s)that provides overlapping coverage with the current cell site (block1110). A first cell site may have one or more antenna arrays 110 thatgenerates a first beam map that has overlapping wireless coverage with asecond beam map of one or more antenna arrays 110 of a second cell site.

Wireless network optimizer 130 analyzes the RSRP_(nc), SINR_(nc), andthe beam data capacity usage of the neighboring cell site(s) to identifywhether the neighbor cell site is less congested (block 1115). Thresholdvalues may be established for the RSRP_(nc), SINR_(nc), and the beamdata capacity usage of the neighboring cell site(s) and may be used foridentifying a current level of congestion relative to the current cellsite.

If the neighboring cell site(s) is not less congested (NO—block 1120),then the process returns to block 1100. If the neighboring cell site(s),having overlapping coverage with the current cell site, is at least ascongested as the current cell site, then there is no need to adjust thehandover threshold to increase handoffs for UEs 115 between the currentserving cell site and a neighboring cell site. As used herein, “handoff”or “handover” refers to the process of transferring an ongoing wirelesscall or data session from a first beam of a first antenna to a secondbeam of a second antenna, where the first antenna and the second antennamay be part of a same antenna array 110 or a different antenna array110. If the neighboring cell site(s) is less congested (YES—block 1120),then wireless network optimizer 130 adjusts the handover thresholdbetween the current cell site and the less congested neighboring cellsite (block 1125). The handover threshold (also referred to herein as“cell selection threshold”) for determining whether to handoff a UE 115from the current cell site to the less congested neighboring cell sitemay be adjusted to increase the likelihood of handoff. For example, ifhandover is based on the received signal level dropping below a certainthreshold value, then the threshold value may be increased such thathandover occurs at a higher received signal level. The adjusted handoverthreshold value may be sent from wireless network optimizer 130 to thecurrent cell site for updating the handover threshold used fordetermining whether to handoff a UE 115 to the neighboring cell site. Insome implementations, the serving cell site (e.g., serving base station105) for a particular UE 115 may direct the UE 115 what handoverthreshold to currently use based on the adjusted handover thresholdvalue received from wireless network optimizer 130.

Wireless network optimizer 130 obtains a current beam data capacityusage and cell capacity usage of cell sites within a cluster of cellsites having overlapping coverage with the current cell site (block1130). For example, if beam maps of adjacent cell sites 1 and 2 indicatethat there is overlapping coverage, then wireless network optimizer 130may determine a current beam data capacity usage per beam, and a currentcell capacity usage, of both of the cell sites.

Wireless network optimizer 130 determines if the beam data capacityusage and the cell capacity usage has been minimized across each cellsite within the cluster of cell sites having the overlapping coverage(block 1135). Therefore, if cell site 1 has beams 1-10, and adjacentcell site 2 has beams 1-20, then wireless network optimizer 130determines if the beam data capacity usage for each of beams 1-10 ofcell site 1, and the beam data capacity usage for each of beams 1-20,has been minimized. Additionally, wireless network optimizer 130determines if the cell capacity usage across cell site 1 (i.e., acrossbeams 1-10), and the cell capacity usage across cell site 2 (i.e.,across beams 1-20), has been minimized. Wireless network optimizer 130,therefore, dynamically adjusts the handover threshold to simultaneouslyminimize the beam data capacity usage and the cell capacity usage acrossthe cell sites having overlapping coverage.

If the beam data usage and cell capacity usage are not minimized acrossthe cell sites of the cluster of cell sites (NO—block 1140), then theprocess returns to block 1125 with wireless network optimizer 130re-adjusting the handover threshold between the current cell site andthe less congested neighboring cell site. Therefore, wireless networkoptimizer 130 may increase or decrease the handover threshold betweenthe beams of a first cell site, and the beams of an overlapping cellsite(s). If the beam data usage and cell capacity usage are minimizedacross the cell sites of the cluster of cell sites (YES—block 1140),then the handover threshold has been dynamically set to optimize networkthroughput in the geographic area of the current cell site, andexecution of block 850 has completed.

The foregoing description of implementations provides illustration anddescription, but is not intended to be exhaustive or to limit theinvention to the precise form disclosed. Modifications and variationsare possible in light of the above teachings or may be acquired frompractice of the invention. For example, while series of blocks have beendescribed with respect to FIGS. 8A, 8B, 9, 10, 11A, and 11B, the orderof the blocks may be varied in other implementations. Moreover,non-dependent blocks may be performed in parallel.

Certain features described above may be implemented as “logic” or a“unit” that performs one or more functions. This logic or unit mayinclude hardware, such as one or more processors, microprocessors,application specific integrated circuits, or field programmable gatearrays, software, or a combination of hardware and software.

No element, act, or instruction used in the description of the presentapplication should be construed as critical or essential to theinvention unless explicitly described as such. Also, as used herein, thearticle “a” is intended to include one or more items. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

To the extent the aforementioned embodiments collect, store, or employpersonal information of individuals, it should be understood that suchinformation shall be collected, stored, and used in accordance with allapplicable laws concerning protection of personal information.Additionally, the collection, storage, and use of such information canbe subject to consent of the individual to such activity, for example,through well known “opt-in” or “opt-out” processes as can be appropriatefor the situation and type of information. Storage and use of personalinformation can be in an appropriately secure manner reflective of thetype of information, for example, through various encryption andanonymization techniques for particularly sensitive information.

In the preceding specification, various preferred embodiments have beendescribed with reference to the accompanying drawings. It will, however,be evident that various modifications and changes may be made thereto,and additional embodiments may be implemented, without departing fromthe broader scope of the invention as set forth in the claims thatfollow. The specification and drawings are accordingly to be regarded inan illustrative rather than restrictive sense.

What is claimed is:
 1. A method, comprising: receiving, at a networkdevice, one or more first key performance indicators (KPIs) associatedwith a cell site providing wireless service within a geographic area;determining, by the network device, at least one first capacity usageparameter associated with the cell site providing the wireless service,wherein the at least one first capacity usage parameter comprises acurrent data capacity usage for each beam of a first antenna array ofthe cell site; and determining, by the network device, placement of anadditional antenna array within the geographic area to provide a certaincoverage and capacity for the geographic area based on the one or morefirst KPIs and the determined at least one first capacity usageparameter.
 2. The method of claim 1, wherein determining the placementof the additional antenna array further comprises: determining, by thenetwork device, a need for the additional antenna array based on the oneor more first KPIs and the determined at least one first capacity usageparameter; and determining, by the network device, an optimum locationwithin the geographic area for the placement of the additional antennaarray.
 3. The method of claim 1, wherein the one or more first KPIs areassociated with wireless communication between multiple beams of thefirst antenna array of the cell site and user equipment devices (UEs).4. The method of claim 1, wherein determining the at least one firstcapacity usage parameter comprises: determining the current datacapacity usage of the cell site based on a number of user equipmentdevices (UEs) being served by the cell site during a current timeinterval and an average active time per beam of the first antenna arrayduring the current time interval.
 5. The method of claim 1, furthercomprising: verifying an optimum placement of the additional antennaarray within the geographic area; and determining, if the placement ofthe additional antenna array is not optimum, another location within thegeographic area for a second placement of the additional antenna array.6. The method of claim 1, further comprising: determining an occurrenceof a change in conditions that affect cell coverage and capacity withinthe geographic area; and based on the occurrence of a change in theconditions: receiving, by the network device, one or more second KPIsassociated with the cell site providing the wireless service within thegeographic area, determining, by the network device, at least one secondcapacity usage parameter associated with the cell site providing thewireless service, and determining, by the network device, placement of asecond antenna array within the geographic area to provide the certaincoverage and capacity for the geographic area based on the one or moresecond KPIs and the determined at least one second capacity usageparameter.
 7. The method of claim 6, wherein the at least one secondcapacity usage parameter comprises a current data capacity usage foreach beam of the second antenna array of the cell site.
 8. The method ofclaim 1, further comprising: dynamically setting, by the network device,a cell selection threshold to optimize network throughput within thegeographic area.
 9. The method of claim 1, wherein the at least onefirst capacity usage parameter is determined by the network device usingthe following:Cell Capacity=∫_(b=0) ^(B)∫_(t=0) ^(T)∫_(u=0)^(U)ƒ(t,ATavg,Modulation(SINRu)) where: the Cell capacity is the currentcell site capacity usage, t=time, ATavg=average active time per beam ofthe cell site's antenna array, u=user equipment device (UE),Modulation(SINRu)=modulation scheme employed by a UE u having a certainSignal-to-Noise-Plus-Interference Ratio (SINR), b=a beam of the cellsite's antenna array, B=maximum number of beams of the cell site'santenna array, T=a time interval, and U=a number of UEs being served bythe cell site within the time interval T.
 10. The method of claim 1,wherein determining the placement of the additional antenna array withinthe geographic area comprises: determining, by the network device, anoptimum location within the geographic area for the placement of theadditional antenna array based on the determined current data capacityusage for each beam of the cell site.
 11. The method of claim 10,wherein the current data capacity usage for each beam of the cell siteis determined, by the network device, using the following:Beam Data Capacity=∫_(t=0) ^(T)∫_(u=0) ^(U)ƒ(t,ATavg,Modulation(SINRu))where: the Beam Data Capacity is the current data capacity usage foreach beam of the cell site, t=time, ATavg=average active time of thebeam associated with an antenna of the cell site's antenna array, u=auser equipment device (UE), Modulation(SINRu)=modulation scheme employedby a UE u having a certain Signal-to-Noise-Plus-Interference Ratio(SINR), T=a time interval, and U=number of UEs served by the beamassociated with the antenna of the cell site's antenna array within thetime interval T.
 12. A network device, comprising: a communicationinterface configured to receive one or more first key performanceindicators (KPIs) associated with a cell site providing wireless servicewithin a geographic area; and a processing unit configured to: determineat least one first capacity usage parameter associated with the cellsite providing the wireless service, wherein the at least one firstcapacity usage parameter comprises a current data capacity usage foreach beam of a first antenna array of the cell site, and determineplacement of an additional antenna array within the geographic area toprovide a certain coverage and capacity for the geographic area based onthe one or more first KPIs and the determined at least one firstcapacity usage parameter.
 13. The network device of claim 12, wherein,when determining the placement of the additional antenna array, theprocessing unit is further configured to: determine a need for theadditional antenna array based on the one or more first KPIs and thedetermined at least one first capacity usage parameter, and determine anoptimum location within the geographic area for the placement of theadditional antenna array.
 14. The network device of claim 12, whereinthe one or more first KPIs are associated with wireless communicationbetween multiple beams of the first antenna array of the cell site anduser equipment devices (UEs).
 15. The network device of claim 12,wherein, when determining the at least one first capacity usageparameter, the processing unit is further configured to: determine thecurrent data capacity usage of the cell site based on a number of userequipment devices (UEs) being served by the cell site during a currenttime interval and an average active time per beam of the first antennaarray during the current time interval.
 16. The network device of claim12, wherein the processing unit is further configured to: determine anoccurrence of a change in conditions that affect cell coverage andcapacity within the geographic area; and based on the occurrence of achange in the conditions: receive one or more second KPIs associatedwith the cell site providing the wireless service within the geographicarea, determine at least one second capacity usage parameter associatedwith the cell site providing the wireless service, and determineplacement of a second antenna array within the geographic area toprovide the certain coverage and capacity for the geographic area basedon the one or more second KPIs and the determined at least one secondcapacity usage parameter.
 17. The network device of claim 16, whereinthe at least one second capacity usage parameter comprises a currentdata capacity usage for each beam of the second antenna array of thecell site.
 18. The network device of claim 12, wherein the processingunit is further configured to: dynamically set a cell selectionthreshold to optimize network throughput within the geographic area. 19.The network device of claim 12, wherein, when determining the placementof the additional antenna array within the geographic area, theprocessing unit is further configured to: determine an optimum locationwithin the geographic area for placement of the additional antenna arraybased on the determined current data capacity usage for each beam of anantenna array of the cell site.
 20. A non-transitory storage mediumstoring instructions executable by a network device with one or moreprocessors, wherein execution of the instructions cause the networkdevice to: receive one or more first key performance indicators (KPIs)associated with a cell site providing wireless service within ageographic area; determine at least one first capacity usage parameterassociated with the cell site providing the wireless service, whereinthe at least one first capacity usage parameter comprises a current datacapacity usage for each beam of a first antenna array of the cell site;and determine placement of an additional antenna array within thegeographic area to provide a certain coverage and capacity for thegeographic area based on the one or more first KPIs and the determinedat least one first capacity usage parameter.